Hobbsnews
Senior Manager, Machine Learning Engineering - Cyber AI
Hobbsnews, New York, New York, us, 10261
11 West 19th Street (22008), United States of America, New York, New YorkSenior Manager, Machine Learning Engineering - Cyber AI
As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You’ll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You’ll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering.Be a part of a dynamic team that’s developing AI capabilities to automate access management processes and remediate risk in real time. You’ll join a group with a robust roadmap, solid investment, and high visibility in the impactful work we do.What you’ll do in the role:The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following:Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams.Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment.Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications.Retrain, maintain, and monitor models in production.Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code.Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI.Use programming languages like Python (Pytorch, Pyspark), Scala and Java.Basic Qualifications:Bachelor’s degree.At least 8 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply).At least 4 years of experience programming with Python, Scala, or Java.At least 3 years of experience building, scaling, and optimizing ML systems.At least 2 years of experience leading teams developing ML solutions.At least 4 years of people management experience.Preferred Qualifications:Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field.4+ years of on-the-job experience with an industry recognized ML framework (scikit-learn, PyTorch, Dask, Spark, or TensorFlow).3+ years of experience developing performant, resilient, and maintainable code.3+ years of experience with data gathering and preparation for ML models.Experience developing and deploying ML solutions in a public cloud (AWS, Azure, or Google Cloud Platform).3+ years of experience building production-ready data pipelines that feed ML models.1+ years of experience working with Cybersecurity related machine learning problems.Ability to communicate complex technical concepts clearly to a variety of audiences.ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents.Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.New York City (Hybrid On-Site): $234,700 - $267,900 for Sr. Mgr, Machine Learning Engineering.This role is also eligible to earn performance-based incentive compensation, which may include cash bonus(es) and/or long-term incentives (LTI). Incentives could be discretionary or non-discretionary depending on the plan.Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the
Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law.If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at
RecruitingAccommodation@capitalone.com . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.For technical support or questions about Capital One's recruiting process, please send an email to
Careers@capitalone.com
.
#J-18808-Ljbffr
As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You’ll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You’ll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering.Be a part of a dynamic team that’s developing AI capabilities to automate access management processes and remediate risk in real time. You’ll join a group with a robust roadmap, solid investment, and high visibility in the impactful work we do.What you’ll do in the role:The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following:Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams.Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment.Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications.Retrain, maintain, and monitor models in production.Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code.Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI.Use programming languages like Python (Pytorch, Pyspark), Scala and Java.Basic Qualifications:Bachelor’s degree.At least 8 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply).At least 4 years of experience programming with Python, Scala, or Java.At least 3 years of experience building, scaling, and optimizing ML systems.At least 2 years of experience leading teams developing ML solutions.At least 4 years of people management experience.Preferred Qualifications:Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field.4+ years of on-the-job experience with an industry recognized ML framework (scikit-learn, PyTorch, Dask, Spark, or TensorFlow).3+ years of experience developing performant, resilient, and maintainable code.3+ years of experience with data gathering and preparation for ML models.Experience developing and deploying ML solutions in a public cloud (AWS, Azure, or Google Cloud Platform).3+ years of experience building production-ready data pipelines that feed ML models.1+ years of experience working with Cybersecurity related machine learning problems.Ability to communicate complex technical concepts clearly to a variety of audiences.ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents.Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.New York City (Hybrid On-Site): $234,700 - $267,900 for Sr. Mgr, Machine Learning Engineering.This role is also eligible to earn performance-based incentive compensation, which may include cash bonus(es) and/or long-term incentives (LTI). Incentives could be discretionary or non-discretionary depending on the plan.Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the
Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law.If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at
RecruitingAccommodation@capitalone.com . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.For technical support or questions about Capital One's recruiting process, please send an email to
Careers@capitalone.com
.
#J-18808-Ljbffr